摘要
为提高传统无线传感器网络节点定位算法精度和定位速度,提出一种基于量子遗传算法的无线传感器网络定位算法。算法通过分析未知节点通信半径范围内的锚节点数量及约束关系,建立节点定位优化模型,对约束范围内节点进行采样,运用传统轮盘赌选择法选取初代种群,最后通过量子旋转门对种群中染色体进行变异及循环迭代,直到达到设定目标值。此后分析现有停车场实时性不高的缺点,提出了一种基于上述定位算法的智能停车场管理系统。以zigbee协议栈为基础,协调器进行组网,参考节点依次加入网络对系统进行检验,结果表明,该无线传感器定位算法可以满足大多数高精度、高实时性应用场合。
In order to improve the precision and response speed of node localization in traditional wireless sensor networks, an algorithm based on quantum genetic algorithm for wireless sensor networks is proposed. The algorithm analyze the number of anchor nodes and constraints beside unknown nodes, and establish a node location optimization model, then use the traditional roulette wheel selection method to select the initial population, finally use the quantum rotation gate variate and iterate population staining body, until the target value is reached. After analyzing the shortcomings of the low real-time performance of the existing parking lots, an intelligent parking management system based on the above-mentioned positioning algorithms is proposed.
作者
盛伟辉
张绪洋
王伟
李鹏鹏
SHENG Wei-hui;ZHANG Xu-yang;WANG Wei;LI Peng-peng(Chang＇an University,Xi＇an 710064,China)
出处
《佳木斯大学学报（自然科学版）》
CAS
2018年第4期614-617,共4页
Journal of Jiamusi University：Natural Science Edition
